title: Modeling phenotypic plasticity in growth trajectories: a statistical framework.
abstract: Phenotypic plasticity, that is multiple phenotypes produced by a single genotype in response to environmental change, has been thought to play an important role in evolution and speciation. Historically, knowledge about phenotypic plasticity has resulted from the analysis of static traits measured at a single time point. New insight into the adaptive nature of plasticity can be gained by an understanding of how organisms alter their developmental processes in a range of environments. Recent advances in statistical modeling of functional data and developmental genetics allow us to construct a dynamic framework of plastic response in developmental form and pattern. Under this framework, development, genetics, and evolution can be synthesized through statistical bridges to better address how evolution results from phenotypic variation in the process of development via genetic alterations.
authors.affiliation: Center for Computational Biology, Beijing Forestry University, Beijing, 100083, China.
authors.forename: Zhong
authors.initials: Z
authors.lastname: Wang
authors.forename: Xiaoming
authors.initials: X
authors.lastname: Pang
authors.forename: Weimiao
authors.initials: W
authors.lastname: Wu
authors.forename: Jianxin
authors.initials: J
authors.lastname: Wang
authors.forename: Zuoheng
authors.initials: Z
authors.lastname: Wang
authors.forename: Rongling
authors.initials: R
authors.lastname: Wu
mesh_terms: D000818:Animals; D019143:Evolution, Molecular; D006128:Growth / Q000235:genetics; D008957:Models, Genetic; D010641:Phenotype; D040641:Quantitative Trait Loci; D013997:Time Factors
keywords: Developmental trajectory; dynamic modeling; functional mapping; logistic growth curve; phenotypic plasticity